Learning Rich Features from RGB-D Images for Object Detection and Segmentation

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dc.contributor.authorSaurabh Gupta
dc.contributor.authorRoss Girshick
dc.contributor.authorPablo Arbeláez
dc.contributor.authorJitendra Malik
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T20:07:52Z
dc.date.available2026-03-22T20:07:52Z
dc.date.issued2014
dc.descriptionCitaciones: 1526
dc.identifier.doi10.1007/978-3-319-10584-0_23
dc.identifier.urihttps://doi.org/10.1007/978-3-319-10584-0_23
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/80167
dc.language.isoen
dc.publisherSpringer Science+Business Media
dc.relation.ispartofLecture notes in computer science
dc.sourceUniversity of California, Berkeley
dc.subjectArtificial intelligence
dc.subjectComputer science
dc.subjectComputer vision
dc.subjectObject detection
dc.subjectPixel
dc.subjectSegmentation
dc.subjectEmbedding
dc.subjectConvolutional neural network
dc.subjectObject (grammar)
dc.subjectPattern recognition (psychology)
dc.titleLearning Rich Features from RGB-D Images for Object Detection and Segmentation
dc.typebook-chapter

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